Genetic Algorithm Parameter Requirements for Detection in MIMO Fading Channels
スポンサーリンク
概要
- 論文の詳細を見る
For multiple-input/multiple-output (MIMO) wireless communications systems employing spatial multiplexing transmission, we evaluate by simulation the parameter (i.e., population size, generation number) value requirements for detection based on genetic algorithm (GA) at the receiver. We assume transmit-correlated Rayleigh or Rician fading with realistic Laplacian power azimuth spectrum as well as azimuth spread (AS) and Rician K-factor selected according to the measurement-based WINNER II channel model, for several relevant scenarios. We first confirm that a GA whose parameters are suitably set converges to maximum-likelihood (ML)-like performance. Then, we study the effects of the number of antennas, modulation constellation size, scenario (i.e., AS and K values), and rank of the deterministic component of the channel matrix on parameter values required for GA in order to converge to ML-like performance. We find that, for poorer channel fading conditions, i.e., poorer achievable MIMO detection performance, the GA converges faster and for smaller population size. Therefore, selecting the GA parameter values according to the channel features may help achieve ML-like performance for lower complexity.
- 信号処理学会の論文
信号処理学会 | 論文
- A study on audio watermarking method based on the cochlear delay characteristics
- Estimation of fundamental frequency of reverberant speech by utilizing complex cepstrum analysis
- 反響音を有する畳み込み形混合過程に対するブラインドソースセパレーションの学習法
- A Model-Concept of the Selective Sound Segregation : A Prototype Model for Selective Segregation of Target Instrument Sound from the Mixed Sound of Various Instruments
- Study of Control Strategy Mimicking Speech Motor Learning for a Physiological Articulatory Model